Figma AI Report 2026: The New Era of Multiplayer Design
1. The center of gravity of AI has shifted from individual efficiency to team collaboration
Three years of data show that changes in roles and collaboration methods are a bigger shift than speed gains.
- This report is based on 8,403 cumulative surveys and 639 qualitative interviews from 2024 to 2026.
- In 2026, 4,392 designers, developers, and PMs from 10 countries, including Korea, took part in the survey.
- 85% of respondents said efficiency had improved, and 70% said they were delivering better results.
- Responses saying AI had a major impact on team collaboration increased sixfold compared with two years ago.
- Developers’ involvement in design increased from 44% to 60%, and designers’ involvement in development increased from 21% to 41%.
- Instead of linear handoffs, a continuous collaboration loop moving back and forth between design and code has taken root.
2. As more AI products increase, the value of design judgment grows
Where production has become easier, design tasks that determine direction, quality, and trust remain.
- 90% of respondents making AI products said design was just as important as before, and 57% said it had become more important.
- Among developers, 65% said design had become more important.
- The share participating in AI projects rose from 65% to 83% in one year, and respondents whose work is more than half related to AI products also increased from 23% to 46%.
- Agentic products can produce different results for the same request, so behavior design, trust building, and error recovery become core design scope.
- The designer’s role also shifts from screen deliverables toward deciding what is worth making and what kind of experience is good.
3. AI adoption splits into four organizational patterns
Rather than whether adoption happens, the speed at which individuals and organizations move determines the perceived outcome.
- Integrated 36%: individuals and the organization move quickly together, with tools, training, and guidelines reinforcing one another.
- Directive-led 27%: the organization starts with strategy and investment first, and the team catches up to the way execution is done.
- Ground-up-led 20%: practitioners use it first, but organizational support lags, widening the gap between expectations and actual launch results.
- Early stage 18%: adoption is slow due to factors such as regulation, organizational structure, and tool accessibility, but it has been cut in half from 36% two years ago.
4. The biggest effects appear when tools and operating systems move together
Organizational support that turns individual experiments into a repeatable team capability accumulates results.
- Integrated organizations were the only group whose actual productivity exceeded the previous year’s expectations.
- Companies providing AI training rose from 28% in 2024 to 54% in 2026, and AI software purchases rose from 38% to 65%.
- Team-level adoption requires four foundations together.
- Prompting skills for making requests more specifically
- Time to test new tools and workflows
- Quality criteria for critically evaluating AI outputs
- A design system ready for AI use, with organized components, tokens, and naming rules
